Stability analysis of neural-network interconnected systems

被引：25

作者：

Hwang, HD ^{[1
]}

Hsiao, FH

机构：

[1] Jin Wen Inst Technol, Dept Elect Engn, Taipei 231, Taiwan

[2] Natl Lien Ho Inst Technol, Dept Elect Engn, Miaoli 360, Taiwan

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 2003年 / 14卷 / 01期

关键词：

interconnected systems; linear difference inclusion (LDI); neural networks (NNs);

D O I：

10.1109/TNN.2002.806643

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the stability problem of a neural-network (NN) interconnected system which consists of a set of NN models. First, a linear difference inclusion (LDI) state-space representation is established for the dynamics of each NN model. Subsequently, based on the LDI state-space representation, a stability criterion in terms of Lyapunov's direct method is derived to guarantee the asymptotic stability of NN interconnected systems. Finally, a numerical example with simulations is given to demonstrate the results.

引用

页码：201 / 208

页数：8

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